Adapting a probabilistic disambiguation model of an HPSG parser to a new domain

  • Authors:
  • Tadayoshi Hara;Yusuke Miyao;Jun'ichi Tsujii

  • Affiliations:
  • Department of Computer Science, University of Tokyo, Tokyo, Japan;Department of Computer Science, University of Tokyo, Tokyo, Japan;Department of Computer Science, University of Tokyo, Tokyo, Japan

  • Venue:
  • IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
  • Year:
  • 2005

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Abstract

This paper describes a method of adapting a domain-independent HPSG parser to a biomedical domain. Without modifying the grammar and the probabilistic model of the original HPSG parser, we develop a log-linear model with additional features on a treebank of the biomedical domain. Since the treebank of the target domain is limited, we need to exploit an original disambiguation model that was trained on a larger treebank. Our model incorporates the original model as a reference probabilistic distribution. The experimental results for our model trained with a small amount of a treebank demonstrated an improvement in parsing accuracy.